doc changes

vision_agent/tools/__init__.py

@@ -9,6 +9,7 @@
  ExtractFrames,
  GroundingDINO,
  GroundingSAM,
+ DINOv,
  ImageCaption,
  SegArea,
  SegIoU,

vision_agent/tools/tools.py

@@ -392,7 +392,7 @@ class DINOv(Tool):
  _ENDPOINT = "https://rkgkjvqgh7vbzjdb23tr7eay4a0vczdo.lambda-url.us-east-2.on.aws"
 
  name = "dinov_"
- description = "'dinov_' is a tool that can detect and segment similar objects with the given input segmentation masks."
+ description = "'dinov_' is a tool that can detect and segment similar objects given a reference segmentation mask."
  usage = {
  "required_parameters": [
  {"name": "prompt", "type": "List[Dict[str, str]]"},
@@ -403,17 +403,17 @@ class DINOv(Tool):
  "scenario": "Can you find all the balloons in this image that is similar to the provided masked area?",
  "parameters": {
  "prompt": [
- {"mask": "balloon_mask1.jpg", "image": "balloon.jpg"},
- {"mask": "balloon_mask2.jpg", "image": "balloon.jpg"},
+ {"mask": "reference_balloon_mask1.jpg", "image": "balloon.jpg"},
+ {"mask": "reference_balloon_mask2.jpg", "image": "balloon.jpg"},
  ],
  "image": "input.jpg",
  },
  },
  {
- "scenario": "Count all the objects in this image that is similar to the provided masked area? image: input.jpg, mask: mask.jpg, mask_image: background.jpg",
+ "scenario": "Count all the objects in this image that is similar to the provided masked area? Image name: input.jpg, Reference mask: mask.jpg, Mask image: background.jpg",
  "parameters": {
  "prompt": [
- {"mask": "obj_mask1.jpg", "image": "background.jpg"},
+ {"mask": "reference_obj_mask1.jpg", "image": "background.jpg"},
  ],
  "image": "input.jpg",
  },